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ITech Research

8

Machine learning and AI

595 000 ₸
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Allocated 34 Quotas

This course guides students from a beginner level to becoming a fully qualified Machine Learning specialist. The first weeks focus on Python programming fundamentals and data manipulation using Pandas, NumPy, and Matplotlib. Subsequent modules cover supervised and unsupervised learning, classification, regression, and clustering applied to real business problems. The curriculum also includes deep learning, computer vision, and natural language processing. The course spans 26 weeks (144 academic hours), delivered online in Kazakh in a group format.

Special condition

Additional Payment. After successful enrollment in the course, the participant is required to pay the remaining part of the tuition fee before the start of classes. Tuition Fee Structure The total cost of the 6-month educational program is 595,000 tenge. The funding is distributed as follows: 400,000 tenge — covered by the targeted grant of the Tech Orda program; 100,000 tenge — provided as internal co-financing by the ITech Research school; 95,000 tenge — constitutes the mandatory co-payment by the student. In the event that the Student fails to fulfill the curriculum requirements (early termination of the agreement at the initiative of the Student, failure to pass the final assessment, failure to obtain the certificate), the Student shall bear responsibility for the misuse of the allocated funds and agrees to pay compensation to the ITech Research institution in the amount of 195,000 tenge.

Course details

level

For beginner

Study format

Online

Entrance exams

No

Duration, in weeks

26

Education language

Kazakh

Qualifications

junior

Skills


Upon completion, students will be able to work with data in Python; apply core ML algorithms (regression, classification, clustering, ensemble methods); build neural networks and CNNs using Keras/TensorFlow; work with NLP, Word Embeddings, and Transformer architectures; design end-to-end ML pipelines from data collection to evaluation; and build a portfolio of 4 real-world projects at a Junior (Strong) ML level.

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